Opporture Lexicon

Voice Recognition

Voice recognition is the ability of a machine or program to receive and interpret dictation. Also called speaker recognition, this technology can understand and execute spoken commands. The rise of AI has driven the application of Voice recognition in many day-to-day applications. Amazon’s Alexa, Microsoft’s Cortana, and Apple’s Siri are classic examples of this technology’s prowess.

Voice recognition works by converting spoken words into digital formats. Next, it understands and interprets the language using Machine Learning and Natural Language Processing.

What are the Diverse Applications of Voice Recognition?

Call Centers

Call centers harness Speech AI to provide the most relevant responses to customer queries and route customers’ calls to respective departments. Applications like voice biometrics are also indispensable in improving customer experience, reinforcing security, and maintaining authentication.

Banking & Finances

Voice recognition-powered service automation is vital in enabling customers to inquire about personal financial details. The technology not only enhances customer interactions and experience but also minimizes the workload for customer service employees.

Telecommunications

All telecommunication processes, like customer interaction, call management, call routing, etc., require voice recognition. The telecommunication sector benefits immensely with shorter response times and finer customer experience, all made possible by voice recognition.

Medicine & Healthcare

Medical professionals benefit from voice recognition-aided hands-free documentation and data entry, resulting in improved patient care. The software also transcribes patient-related voice notes and bridges the communication gap between healthcare providers and disabled patients.

Smart Homes & IoT Devices

All smart home devices like smart TVs, voice-activated locks, cleaning devices, and alarm systems are powered by voice recognition technology. It also acts as an interface for robotic vacuum cleaners, smart irrigation systems, and refrigerators.

Automotive Industry

Voice recognition has revolutionized the automotive sector by enabling hands-free vehicle control and smart navigation systems. Users can make phone calls or modify the music system settings with voice commands. It is, therefore, less likely that the driver will be distracted and safety will be compromised.

FAQs

1. How does voice recognition function?

In computers, voice recognition software requires an analog-to-digital or A/D conversion for the analog audio to be converted to digital signals. The computer requires a digital database of words and syllables to decode and compare the data to signals. Voice recognition models analyze speech through the hidden Markov model or neural networks. These tools rely on AI to differentiate between speakers.

2. What is the algorithm used for voice recognition?

Voice recognition uses algorithms like:

Hidden Markov Models or HMMs to model the temporal speech variability and to match phonetic patterns with the input speech signals.
Deep Neural Networks, or DNNs, can learn the intricate structures in audio signals.
Convolutional Neural Networks, or CNNs, process an audio signal’s spectrogram.

3. What are the types of voice recognition?

There are two types of voice recognition:

1. Text-dependent voice recognition recognizes the speaker’s predetermined voice passphrases. Dependent speech recognition systems can perform at an accuracy of 98% or more.

2. Text Independent analyzes conversational speech without predetermined passphrases. Independent speech recognition can deliver 95% accurate results for smaller populations.

4. What are the drawbacks of voice recognition software?

Voice recognition software is far from perfect and can misunderstand the speech. Other issues include:

Mistakes with pronunciation, grammar, and punctuation
Unwanted background noise
Unwanted accents
Wrong formatting

Users must train the software to recognize their voice and master the technology’s commands and keywords.

5. How do you create a voice recognition system?

To create a voice recognition system, you need to use the:

Automatic Speech Recognition (ASR)
Natural Language Processing (NLP)
Audio processing
Background noise suppression
Speaker diarization
Activity detection

You can optimize sample rates and normalize recording volume to improve ASR quality.